基于GA-SVM方法的行业协会信用度评价分析  

ANALYSIS ON THE CREDIT EVALUATION OF INDUSTRY ASSOCIATION BASED ON GA-SVM METHOD

作　　者：汪磊[1,2] 杨希 黄蓉静 

机构地区：[1]安徽工程大学,安徽芜湖241000 [2]合肥工业大学,安徽合肥230009

出　　处：《巢湖学院学报》2017年第4期44-49,共6页Journal of Chaohu University

基　　金：安徽省高等学校人文社会科学研究重点项目(项目编号:SK2016A0114);安徽工程大学"地方政府与社会治理创新研究中心"招标项目(项目编号:DS2015D02)

摘　　要：近年来,社会公众对于行业协会信用问题的关注越来越多。开展行业协会信用评价分析,不仅有助于提高信用评价结果的准确度,对行业协会精准"画像",同时可以"以评促改",提高行业协会的规范化管理水平。因此,围绕行业协会信用度评价开展分析,科学构建了行业协会信用度评价系统,运用支持向量机分类方法建立行业协会信用度评价模型,并引入遗传算法对模型进行参数寻优,最后,开展实证分析并对行业协会提高信用度方面的决策提出具体建议。In recent years, the issue of association credit has attracted more attention of the public. Generally, the analysis of association credit evaluation might not only contribute to the accuracy of evaluation results, but also successfully raise the standardized management level of industry association in the process of credit evaluation. Thus, this paper focuses on the issue of credit evaluation on industry association, analyzes an index system of credit evaluation, develops an evaluation model of industry association based on SVM, introduces GA method for parameter optimization, and further proposes some specific suggestions on the improvement of association credit.

关 键 词：行业协会 遗传算法 支持向量机 信用评价 

分 类 号：C916[经济管理]